package com.atguigu.day05;

import com.atguigu.bean.WaterSensor;
import org.apache.flink.api.common.functions.AggregateFunction;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.api.java.tuple.Tuple;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.datastream.WindowedStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.assigners.ProcessingTimeSessionWindows;
import org.apache.flink.streaming.api.windowing.assigners.TumblingProcessingTimeWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;

public class Flink05_TimeWindow_Tumbling_AggFun {
    public static void main(String[] args) throws Exception {
        //1.获取流的执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        env.setParallelism(1);

        //2.从端口读取数据
        DataStreamSource<String> streamSource = env.socketTextStream("localhost", 9999);

        //3.将数据转为JavaBean
        SingleOutputStreamOperator<WaterSensor> map = streamSource.map(new MapFunction<String, WaterSensor>() {
            @Override
            public WaterSensor map(String value) throws Exception {
                String[] split = value.split(",");
                WaterSensor waterSensor = new WaterSensor(split[0], Long.parseLong(split[1]), Integer.parseInt(split[2]));
                return waterSensor;
            }
        });


        //4.对相同id的数据聚合到一块
        KeyedStream<WaterSensor, Tuple> keyedStream = map.keyBy("id");

        // 5.开启一个基于时间的滚动窗口 窗口大小为5S
//        WindowedStream<WaterSensor, Tuple, TimeWindow> window = keyedStream.window(TumblingProcessingTimeWindows.of(Time.seconds(5)));
        WindowedStream<WaterSensor, Tuple, TimeWindow> window = keyedStream.window(ProcessingTimeSessionWindows.withGap(Time.seconds(3)));

        //TODO 6.使用增量聚合函数AggFun对vc做累加计算
        window.aggregate(new AggregateFunction<WaterSensor, Integer, String>() {
            //创建累加器
            @Override
            public Integer createAccumulator() {
                System.out.println("创建累加器");
                return 0;
            }

            //累加操作
            @Override
            public Integer add(WaterSensor value, Integer accumulator) {
                System.out.println("累加操作");
                return value.getVc() + accumulator;
            }

            //获取最终结果
            @Override
            public String getResult(Integer accumulator) {
                System.out.println("获取最终结果");
                return accumulator + "";
            }

            //合并累加器
            //只在会话窗口的特殊场景下会调用
            @Override
            public Integer merge(Integer a, Integer b) {
                System.out.println("合并累加器");
                return a + b;
            }
        }).print();

        env.execute();
    }
}
